An Integrated Directional Drilling Simulator with Steering Advisor and Self-Learning Algorithm

Abstract

The industry has recently put a significant emphasis on optimizing the directional drilling process to reduce non-productive time (NPT) and improve well-bore quality. Mud motors are widely used due to their low operational cost and high reliability. In this paper, a drilling advisory system for mud motors has been developed to provide steering recommendations in real time to maintain smooth wellbore trajectories respective to a given well plan while satisfying operational constraints. The drilling advisory system, which was tested both offline and online on 20 of runs across North America and globally, provides reliable steering decisions relative to the surveys and real-time data, when available. This capability revolutionizes the drilling industry by providing a tool that guides directional drillers toward improving efficiency, consistency, and quality. Moreover, the advisory system serves as the core to the development and implementation of a fully autonomous drilling system.